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| 基于最优小波包的水轮发电机组振动信号特征提取方法 | |
| 引用本文： | 严平,李书明,马安.基于最优小波包的水轮发电机组振动信号特征提取方法[J].电力自动化设备,2008,28(2):70-72. |
| 作者姓名： | 严平 李书明 马安 |
| 作者单位： | 1. 国电南京自动化股份有限公司,江苏,南京,210003 2. 国电南京自动化股份有限公司,江苏,南京,210003;河海大学,水利水电工程学院,江苏,南京,210098 3. 山西省电力公司,晋城供电分公司,山西,晋城,048006 |
| 摘 要： | 水轮发电机组振动信号的在线监测是实现机组状态检修方法的关键。在分析了水轮发电机的机组振动信号特征后,提出采用db1小波进行振动信号的特征提取,在信号分析中主要应用shannon熵。小波包的构造是基于函数空间的正交剖分;最佳小波包基的选择就是应用最优的分解方法和有效的算法寻找出最小熵标准;给出了机组振动信号特征提取的步骤。根据所构造的最优小波包对机组振动信号进行分解并运用能量特征提取分析方法对机组振动信号进行特征提取。 |
| 关 键 词： | 发电机组 最优小波包 振动信号 特征提取 |
| 文章编号： | 1006-6047（2008）02-0070-03 |
| 收稿时间： | 2007-11-16 |
| 修稿时间： | 2007-12-06 |
Feature extraction of water turbine vibration signal based on optimal wavelet packet |
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| YAN Ping,LI Shuming,MA An.Feature extraction of water turbine vibration signal based on optimal wavelet packet[J].Electric Power Automation Equipment,2008,28(2):70-72. | |
| Authors: | YAN Ping LI Shuming MA An |
| Abstract: | Online monitoring of water turbine vibration signals is the basis of its conditional maintenance.Based on the analysis of signal features,wavelet db1 is put forward to extract the features of water turbine vibration signals.Mainly the shannon entropy is used in feature extraction.Wavelets package construction is based on the orthogonal subdivision of function space.The selection of optimal wavelets is to find the minimal entropy using optimal division methods and effective algorithm.The steps of vibration signal feature extraction are given.The constructed optimal wavelet package is used to divide the vibration signals of water turbine and the energy feature analysis is used to extract the features of water turbine vibration signals. |
| Keywords: | generation set optimal wavelet packet vibration signal feature extraction |
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